Abstract: Techniques are provided for managing metadata of a storage system. A storage control system manages a storage metadata structure which comprises metadata items for accessing data items in a storage system comprising a persistent write cache and a primary storage. The storage metadata structure comprises a first metadata structure that is configured to organize metadata items received from the write cache at a first granularity, and a second metadata structure that is configured to organize metadata items received from the first metadata structure at a second granularity, wherein the second granularity is greater than the first granularity. The storage control system utilizes the storage metadata structure to access data items in the persistent write cache and the primary storage.

Abstract: Techniques for creating and establishing a configuration of connections between an initiator system and a target system can use whitelisted target ports, wherein the configuration only includes connections to selected whitelisted target ports. Automatic login of each initiator to all zoned and discovered target ports can be avoided where, alternatively, an on-demand or needs-based login can be performed by having each initiator only log into its whitelisted target ports. In this manner, better resource usage and scalability can be obtained using the techniques of the present disclosure. In one embodiment, the whitelisted target ports can be determined automatically using an intersection of target port lists obtained using a control path connection and using a fabric nameserver query. The configuration including the whitelisted targets can be persistently stored on the initiator system to enable restoration of the whitelisted targets across reboots and resets of the initiator system.

Abstract: A system of one or more computers can be configured to facilitate the design of a service. The disclosed system may operate to add a process block to a service design structure for the service. The process block is provided to a trained AI/ML process prediction model. The trained AI/ML process prediction model suggests one or more further process blocks for addition to the service design structure based, at least in part, on the addition of the process block to the service design structure. In certain embodiments, a process block is selected from the suggested one or more further process blocks and added to the service design structure. Other embodiments of this aspect of the disclosure include corresponding computer systems, apparatus, and computer programs recorded on one or more computer storage devices, each configured to perform the actions of the methods.

Abstract: In a distributed ledger (DLT) network, a transaction, related to movement of a monitored entity from a first party's location to a second party's location, is monitored. The transaction is associated with a respective real-time status and with at least a first predetermined milestone. Sensor outputs from an IoT enabled sensor that is operably coupled to the monitored entity, are received while the monitored entity is located remotely from the first and second parties during its movement from the first location to the second location. Updates to a real-time status of the monitored entity, relating to progress towards a milestone, are determined based on the received sensor outputs. The transaction is updated, in real time, on the DLT network when the milestone is reached. Information is communicated relating to the update of the transaction and the first predetermined milestone, in real-time, to the first party and the second party.

Abstract: In one or more embodiments, one or more systems, one or more methods, and/or one or more processes may receive a scaling factor and a retention time power law coefficient associated with a solid state drive (SSD); determine a first raw bit error rate (RBER) value for the SSD at a first time; extrapolate a second time at which a second RBER value for the SSD would reach a maximum RBER value if left unpowered, based at least on the first raw bit error rate value, the scaling factor, and the retention time power law coefficient; and provide the second time at which the second RBER value for the SSD would reach the maximum raw bit error rate value if left unpowered to at least one of an information handling system (IHS), IHS firmware, a baseboard management controller of the IHS, and an application executing on the IHS.

Abstract: End user interactions at a display are monitored for predetermined conditions to provide augmentation of display presentation by a red light that illuminates in the 650 to 800 nm range, such as at substantially 670 nm. Instructions stored in non-transient memory and executed on a processor present visual images of varied color contrast and evaluate end user inputs to determine an end user visual acuity. Over time and use of the display and red light, end user visual acuity is periodically tested to evaluate the effectiveness of red light illumination to restore visual acuity.

Abstract: An information handling system peripheral camera ensures privacy with a cover that minimizes distance of a camera module to a front opening of the camera housing. For instance, opposing cover members rotate about geared ends that engage to translate rotation between the members, where the members meet over a camera opening to block capture of visual images and move to opposing sides to expose the camera module. In an alternative embodiment, a rotating shutter arrangement selectively covers the camera for security and also covers a microphone to provide security against unauthorized audible access through the camera. Selective covering and exposing of a camera module, infrared camera, microphone and user presence detection sensor support adaptive security at a camera based upon end user context.

Abstract: A load balancing algorithm and cluster configuration details are stored at each of a set of namespace nodes of a cluster hosting a deduplicated file system. Upon a client connecting to a namespace node, a server-initiated communication channel is established between the namespace node and the client over which updates to the load balancing algorithm, cluster configuration details, or both are sent. The load balancing algorithm and cluster configuration details are sent to the client, thereby allowing the client to determine according to the load balancing algorithm and cluster configuration details, which particular namespace node should handle a particular file system operation. Thereafter, each connected client is immediately notified of changes to the cluster such as node or service additions or deletions or software upgrades to the cluster so that each client can use the updated information to conduct load balancing.

Abstract: Methods and systems for managing the performance of workloads in a distributed system are disclosed. The distributed system may include any number of clients and deployments where workloads may be performed. The workloads may be performed by deploying container instances to the deployments. The container instances may perform the workload when deployed. It may be challenging to ascertain whether a container instance, container image on which the instance is based, and/or corresponding build file used to obtain the container image should be trusted. Metadata block chains may be used to ascertain whether container instances should be deployed to service the workload requests.

Abstract: Embodiments of the present disclosure relate to a computer-implemented method, device, and computer program product. The method includes: determining, based on a set of user behavior data over a first time period, a set of behavioral features for a user behavior over the first time period. The method further includes: determining, based on the set of behavioral features, a set of anomaly scores for the user behavior according to an anomaly detection model. The anomaly detection model is trained based on user behavior data over a second time period. The method further includes: updating a previously determined anomaly score threshold based on comparison of the determined set of anomaly scores with the anomaly score threshold. The anomaly score threshold is used for indicating whether the user behavior is anomalous. By continuously updating the anomaly score threshold, the solution uses the updated anomaly score threshold for anomaly detection of user behavior.

Abstract: Presented are efficient systems and methods for automatically detecting and configuring network connections in Fibre Channel (FC) and similar networks. In various embodiments, this is accomplished by using an I/O module (IOM)'s fabric login (FLOGI) response or FLOGI request to identify the type of an uplink interface as either FC Gateway or FC Direct Attach, determining whether server interfaces coupled to the TOM support FCoE, and then, automatically configuring server interfaces based on the identified type of uplink interface.

Abstract: A method in an illustrative embodiment of the present disclosure includes determining, utilizing a first diagnosis model deployed in a storage system, whether a cause of a fault belongs to environmental factors. The method further includes determining, responsive to determining that the cause of the fault belongs to the environmental factors, whether the fault can be solved locally in the storage system. The method further includes sending, responsive to determining that the fault cannot be solved locally in the storage system, the fault to a second diagnosis model, wherein the first diagnosis model is obtained by distilling the second diagnosis model. According to the method for fault diagnosis of the present disclosure, particular faults can be diagnosed and solved locally in a storage system, so that the workload of a customer support team of the storage system in a cloud can be reduced.

Abstract: A method comprises collecting data corresponding to a plurality of components in a system, wherein the data comprises information about one or more issues with the plurality of components. The data is analyzed and categorized based at least in part on the analysis. In the method, one or more application programming interfaces (APIs) are selected to monitor respective statuses of the plurality of components, wherein the selection is based at least in part on the categorization of the data, and the data is pushed to the one or more APIs.

Abstract: An apparatus comprises at least one processing device configured to monitor, by a first service in a service chain, a first set of processing queues comprising two or more different processing queues associated with two or more different priority levels. The processing device is also configured to process, by the first service, a given portion of data stored in at least one of the two or more different processing queues in the first set of processing queues. The processing device is further configured to determine prioritization information associated with the given portion of the data and to select, based on the prioritization information, a given one of two or more different processing queues in a second set of processing queues associated with a second service in the service chain, and to store the given portion of the data in the given processing queue in the second set of processing queues.

Abstract: A system can maintain information indicative of prohibited computer operations, wherein the information is accessible to respective computing clusters of a group of computing clusters, and wherein the information is stored separately from the group of computing clusters. The system can obtain, by a service of a first computing cluster of the group of computing clusters, the information. The system can, in response to receiving, at the first computing cluster, a request to perform an operation on a first computer of the first computing cluster, in response to determining, based on the information, that the operation is prohibited, prevent the operation from occurring; and, in response to determining, based on the information, that the operation is not prohibited, permit the operation to occur.

Abstract: An apparatus comprises a processing device configured to select first and second versions of at least a given portion of a web application, to obtain first and second document object model structures of the first and second versions of the given portion of the web application, and to generate, based at least in part on the first and second document object model structures, first and second tree structures, the first and second tree structures comprising nodes representing web elements of the given portion of the web application. The processing device is also configured to identify node differences between the first and second tree structures, to generate information characterizing differences between web elements in the given portion of the first and second versions of the web application, and to initiate automated action based at least in part on the generated information.

Abstract: Within a domain such as a data center, host server activity monitors running on storage nodes observe meaningful commands sent by host servers to the storage nodes. Inactivity indicated by failure of any of the activity monitors to receive a meaningful command from a host server within a predetermined time limit prompts generation of a message that identifies that host server as possibly being unused. The host server activity monitors are also configured to identify as a possible unused host server any host server that is zoned for at least one of the storage nodes but not masked to any storage objects. If a quiescent host server becomes active, as indicated by resumption of sending meaningful commands to one of the storage nodes, then a message warning of a potential malicious attack is generated.

Abstract: A system, method, and computer-readable medium are disclosed for performing a data center monitoring and management operation. The data center monitoring and management operation includes: identifying data center asset data to monitor; collecting data center asset data; and, performing an adaptive update scheduling operation, the adaptive update scheduling operation adaptively adjusting a prioritization and frequency of data center asset data collection to provide adapted data center asset data.

Abstract: Targetless snapshots of a storage object are characterized in terms of likelihood of access using time-series analysis. Metadata of replication data structures of individual targetless snapshots is maintained in either uncompressed or compressed form based on the characterization of the targetless snapshot. Metadata is compressed at the page level, with same-pages of all replication data structures of cold snapshots of a storage object being compressed together. Compressed pages of targetless snapshot metadata are maintained of storage devices selected based on storage device performance and the time-series characterization of the targetless snapshot.

Abstract: A system for network management comprising a silicon management system operating on a processor that causes the processor to load one or more algorithms stored in a non-transient data memory to cause the processor to identify a version for a plurality of silicon data processing devices and to implement an update to one or more of the silicon data processing devices, a chipset management system operating on a processor that causes the processor to load one or more algorithms stored in a non-transient data memory to cause the processor to identify a version for a plurality of chipsets, each chipset associated with one of the silicon data processing devices and to implement an update to one or more of the chipsets and a boot system configured to cause a system associated with the updated silicon data processing devices and the updated chipsets to reboot.